enbis presentation(2)

06 /09/2011

Research Project “ Methodology for scaling Applied

Statistics as Competitive Advantage”

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Igor BARAHONA TORRES. And

Alex RIBA CIVIL

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IN THIS PRESENTATION.

INTRODUCTION

STATE OF THE ART

RESEARCH OBJECTIVES

THE DRAFT OF A SCALE

THE METHODOLOGY

CONCLUSIONS

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IN THIS PRESENTATION.

INTRODUCTION

STATE OF THE ART

RESEARCH OBJECTIVES


THE METHODOLOGY

CONCLUSIONS

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INTRODUCTION

At first, some basic information about Catalonia is provided

441,858 756,293 810,564 5,526,536 7,535,251

47,150,819

Lleida Girona Tarragona Barcelona Cataluña España

Population

Catalonia is located in the north East of Spain

It is composed for 4 regions

Catalonia represents around 16% of the total population of Spain

Around 73% of Catalonia's population live in Barcelona

IDESCAT & lNE (2011)

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INTRODUCTION

WHAT IS THE BUSINESS

MANAGEMENT ENVIRONMENT

LIKE TODAY?

BETTER INFORMATION SYSTEMS. (MRP, CRM, ERP, etc)

MORE COMPLEXITY AND UNCERTAINTY

INTERNET IS AVAILABLE FOR MOST OF THE COMPANIES

MORE POWERFUL COMPUTERS

BIGGER AMOUNT OF DATA AVAILABLE FOR ANALYSIS

Burby & Atchison (2007), Petroni & Braglia. (2000) & Roberts (1990)

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INTRODUCTION

IF COMPANIES HAVE MORE DATA AND BETTER

INFORMATION SYSTEMS

HOW CAN HIGHER

PROFITS BE OBTAINED?

THE POINT IS..........

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STATE OF THE ART

INTRODUCTION

STATE OF THE ART

RESEARCH OBJECTIVES


THE METHODOLOGY

CONCLUSIONS

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APPLIED STATISTICS IN BUSINESS. WHAT IT IS?

One approach is to understand it as a process with INPUTS and OUTPUTS.

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WHAT IS APPLIED STATISTICS IN BUSINESS MANAGEMENT?

Extensive use of data and statistical methods

To understand the past performance

To reduce uncertainty

To forecast the future and to predict behaviors.

Better decision making

Evidence-based decision making

OUTPUTS

ADDED VALUE

INPUTS

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Systematic Thinking

Management support

To remove obstacles

To provide the technical human and financial resources

.

To encourage the staff to be involved in the project

Emergence

Hierarchy

Communication

Control.

THERE ARE 4 KEY ELEMENTS TO SUCCESS

Jackson (1992) & Yeo (1993)

McDonough (2000), Banks (1993) & Deming (2000)

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2

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Competitive advantage

Data exploitation

Cost Leadership.

Niche strategies

Differentiation

Privileged location

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Integration from multiple sources

Efficiency in Data structure

Accessibility to data

Security and privacy

Porter (1998)

Davenport. & Harris (2007). Evantage Consulting & Janis, A. (2008)

THERE ARE 4 KEY ELEMENTS TO SUCCESS

3

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HOW DO THESE KEY FACTORS INTERACT?

ASBM

COMPETITIVE ADVANTAGE

SYSTEMATIC THINKING

MANAGEMENT SUPPORT

DATA EXPLOITATION

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WHICH AREAS USE MORE APPLIED STATISTICS?

INSIDE THE COMPANY

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RESEARCH OBJECTIVES

INTRODUCTION

STATE OF THE ART

RESEARCH OBJECTIVES


THE METHODOLOGY

CONCLUSIONS

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RESEARCH OBJECTIVES

1. To create a quantitative scale for ranking a sample of Catalonian Companies according to their 1) Data exploitation with statistical tools, 2) Competitive advantage, 3) Management support and 4) Systematic thinking

2. To apply the created scale on a previously defined sample of Catalonian Companies, in order to know their capacity for applying statistics to decision making

3. To find out associations between each analysed variable. The impact of data exploitation, Competitive advantage, Management support and Systematic thinking on decision making

4. To validate the methodology to upgrade companies on the proposed scale and to make applied statistics a competitive advantage

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THE DRAFT OF ONE SCALE

INTRODUCTION

STATE OF THE ART

RESEARCH OBJECTIVES


THE METHODOLOGY

CONCLUSIONS

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SOME BASIC IDEAS OF ONE POSSIBLE SCALE

1. The proposed scale has 5 possible levels

2. At level 1 we find companies that do not use any statistical methods

3. At level 5 we find companies that use applied statistics as a strategic support for their competitive advantage.

4. At levels 2, 3 and 4 we find companies that are improving their use of statistical methods

5. A survey, in depth interviews and on site study cases will be used to validate the scale

HIGHLIGHTS

SOME BASIC IDEAS OF ONE POSSIBLE SCALE

STATISTICAL IGNORANCE.

LOCAL AND INDIVIDUAL

EFFORTS

STATISTICAL ASPIRATIONS

STATISTICAL ENGINEERING

STATISTICS AS COMPETITIVE ADVANTAGE

Decision making process is based mainly on past experience and subjective evidence

To pick up reliable and valid data

Statistics support only specific activities in the company. Those efforts are usually isolated with local impact.

To increase and improve interactions between local applications

The first level of using statistics as Competitive Advantage. Leadership, Systematic Thinking and Data Quality are introduced.

To develop use of 4 key drivers to improve business results

All decisions in the company are made through Statistical analysis

To make sure that statistics is used at Strategic, Tactical and Operative levels.

Mastering the use of statistics,. It provides important support to develop a successful competitive advantage

To obtain the leadership in the market.

1

2

4

3

5

NAME DESCRIPTION TARGET

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THE METHODOLOGY

INTRODUCTION

STATE OF THE ART

RESEARCH OBJECTIVES


THE METHODOLOGY

CONCLUSIONS

• THE QUESTIONNAIRE

• IN DEPTH INTERVIEWS

• ON SITE CASE STUDIES

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THE METHODOLOGY

THE QUESTIONNAIRE

IN-DEPTH INTERVIEWS

ON-SITE CASES STUDIES

THE METHODOLOGY

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THE QUESTIONNAIRE

THE QUESTIONNAIRE

IN-DEPTH INTERVIEWS


THE METHODOLOGY

This is the questionnaire s structure There are 7 sections and 48 ITEMS in the questionnaire, as it is shown in the following table:

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section number of ITEMS

General information about the company 4

Competitive Advantage 3

Data exploitation and usage 5

Management support 5

Systemacic Thinking 5

Statistical Methods inventory 19

Company´s departments 11

Total 48

THE QUESTIONNAIRE

https://www.surveymonkey.com/s/surveyEAGE_english

https://www.surveymonkey.com/s/surveyEAGE_english

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WHO IS IT BEING SENT TO?

1003 questionnaires were sent in the last 2 month

82 questionnaires were received by August 31

Questionnaires still need to be sent to 5208 companies

Target Group size Number of responses

Response rate

Investigar en España

1,264 6 0.05%

Estadística para todos

425 6 1.4%

Investigación y Estadística 237 5 2.1%

250 27 11%

1,003 38 3.8%

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IS OUR QUESTIONNAIRE VALID AND RELIABLE?

CONBRACH’S ALPHA

This is how Cronbach’s Alpha is interpreted:

Cronbach (1951), Hernández (2006) Condesa, (2000) & Castro, P.L. (1989)

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Here we have Cronbach’ s values for each section

COMPETITIVE ADVANTAGE

DATA EXPLOITATION

MANAGEMENT SUPPORT

SYSTEMATIC THINKING

TECHNICAL STATISTICS INVENTORY

IS OUR INSTRUMENT VALID AND RELIABLE?

0.6062

0.8857

0.8806

0.7420

0.9544

The calculations of Cronbach’s values allowed us to guarantee that our questionnaire is reliable.

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IN-DEPTH INTERVIEWS

THE QUESTIONNAIRE

IN-DEPTH INTERVIEWS


THE METHODOLOGY

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IN-DEPTH INTERVIEWS

WHY DO WE DO DEPTH

INTERVIEWS?

To include in the research, issues that are neither evident in the literature nor the questionnaire.

To validate or refute the findings of the questionnaire

To find perception from Business s owners, Managers and Academics

To find aspects of Applied Statistics which are undetectable with the questionnaire

The Multicriteria Decisions Analysis used by Nutt, King y Lawrence (2010) is also taken as reference for carrying out the interviews

The concepts developed by French , Maule y & Papamichail (2009) will be used for designing and preparing the interview

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IN-DEPTH INTERVIEWS

In the following table shows how interviews are classified according to the type of stakeholder

The total number of interviews is not definitive and it will be altered according the homogeneity of the responses obtained

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THE QUESTIONNAIRE

IN-DEPTH INTERVIEWS


THE METHODOLOGY

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The survey and interviews will be the input for the methodology that can be implemented in three study cases.

WHY DO WE DO ON-SITE

CASES STUDIES?

To implement the key drivers for the increase in the use of applied statistics

To validate or refute the findings obtained with questionnaires and interviews

To build a practical and helpful methodology accessible to any Consultant, Practitioner or Academic

To replicate and to reproduce the key elements identified

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ON-SITE CASES STUDIES FLOW CHART

This is the flow chart that will be used for carrying out the on-site cases studies

INITIAL ASSESSMENT

One level at the scale

Level 5

Level 4

Level 3

Level 2

Level 1

Actions to upgrade

from L1 to L2

Actions to upgrade

from L2 to L3

Actions to upgrade

from L3 to L4

Actions to upgrade

from L4 to L5

To maintain and to

improve

• Management support

• Systematic Thinking

• Data exploitation and usage

• Competitive advantage

• Statistical Methods inventory

FINAL ASSESSMENT

Is it improved?

NO

YES

• To keep records • To replicate • To standardize

• To review •To identify • To point out

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THE CONCLUSIONS

INTRODUCTION

STATE OF THE ART

RESEARCH OBJECTIVES


THE METHODOLOGY

CONCLUSIONS

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FIRST ROUND CONCLUSIONS

THERE IS EVIDENCE TO DEMONSTRATE THE RISING OF THE USE OF APPLIED STATISTICS IN BUSINESS IN THE LAST 20 YEARS

THIS REPRESENTS A UNIQUE OPPORTUNITY FOR COMPANIES

WE ARE WORKING WITH A QUESTIONNAIRE THAT IS VALID AND RELIABLE

THIS METHODOLOGY WILL BE A UNIQUE TOOL FOR THE INCREASE IN THE USE OF APPLIED STATISTICS IN BUSINESS MANAGEMENT

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THE END OF PRESENTATION

THANKS!

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RADAR CHART

S. Thinking

M. Support

Statistical Methods Use of Data

C. Advantage

S. Thinking

M. Support

Statistical Methods Use of data

C. Advantage

CHECKING AND TESTING

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36


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INTRODUCTION

Industries 230,301 Construction

510,243

Services 2,550,719

Total number of companies at Spain and Catalonia

Industries 44776

Construction 97019

Services 477883

Catalonia concentrates the 19% of total number of companies in Spain

Given this, the size of the population for this research is 619,780 companies

The percentage of companies in services is equal to 77% for both, Spain and Catalonia

SPAIN 3,291,263

CATALONIA 619,678

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Reliability is related to the precision and stability of the questionnaire

Validity is related with the Questionnaire’s capacity to measure all the variables and issues for which it was created

The Conbrach’s Alpha is calculated and interpreted to measure reliability

In order to guarantee the validity, an operational definition of variables is used

HIGHLIGHTS

Cronbach (1951), Hernández (2006) Condesa, (2000) & Castro, P.L. (1989).

......

......

......

......

......

......

...... 39

HOW CRONBACH’S ALPHA IS CALCULATED?

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CONBRACH’S ALPHA

Data Exploitation

HOW CRONBACH’S ALPHA IS CALCULATED?

1. Reliability for DATA EXPLOITATION section is VERY HIGH .

2. Additionally all the correlations between ITEMS have positive values

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CONBRACH’S ALPHA 1. The mathematic definition of Cronbach s alpha is:

2. This is how Cronbach’s Alpha is interpreted:

3. Additionally one Cronbach’s Alpha was calculated for each variable that is intended to measure

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